Method, apparatus and device for generating target detection information

ABSTRACT

Provided is a method for generating target detection information, including detecting target objects around the vehicle by multiple different types of sensors, and determining the detection targets representing a same target object, detected by the different types of sensors, by spatial position and time tracing. With taking the target object as the detection result, the target detection information generated for the detection result includes a spatial matching confidence of the detection result in the current detection period, a time matching confidence of the detection result, and target detection information on each of the detection targets representing the detection result, collected by the sensor detecting the detection target in a dimension corresponding to the sensor.

This application claims priority to Chinese patent application No.201611259559.1 titled “METHOD, APPARATUS AND DEVICE FOR GENERATINGTARGET DETECTION INFORMATION” and filed with the Chinese StateIntellectual Property Office on Dec. 30, 2016, which is incorporatedherein by reference in its entirety.

FIELD

The present disclosure relates to the field of information processingtechnology, and particularly to a method, an apparatus and a device forgenerating target detection information.

BACKGROUND

With development of electronization and intelligentization of vehicles,many different types of sensors are arranged on the vehicles, to sensesurrounding environment and detect target objects around the vehicle.Different types of sensors detect target objects according to differentdetection mechanisms, and thus have different advantages anddisadvantages. Conventionally, target objects around the vehicle aredetected by a single type of sensor, that is, target detectioninformation for describing characteristics of the target object iscollected by a same sensor. However, the inventor found that targetdetection information in some dimensions may cannot be collected by asingle type of sensor or the collected target detection information insome dimensions may not be accurate, or even in some cases the targetobject cannot be detected. Therefore, by using a single type of sensorto detect target objects, false detection or missing detection mayoccur, and accurate and complete target detection information inmultiple dimensions cannot be obtained.

SUMMARY

A technical problem to be solved by the present disclosure is to providea method, an apparatus and a device for generating target detectioninformation, to reduce false detection rate and missing detection rateof target objects, and provide accurate and complete target detectioninformation in multiple dimensions.

In an aspect, it is provided a method for generating target detectioninformation, including:

determining, in a unified plane coordinate system, spatial positions ofinitial detection targets detected by a plurality of different types ofsensors in a current detection period;

matching spatial positions of initial detection targets to be matcheddetected by every two of the plurality of different types of sensors inthe current detection period, and determining the initial detectiontargets under a detection result as result detection targets, whereinspatial positions of any two of the result detection targets under thedetection result are matched with each other; and

generating target detection information of the detection result, whereinthe target detection information of the detection result comprisestarget detection information on each of the result detection targets,which is collected by the sensor detecting the result detection targetin a dimension corresponding to the sensor, and each of the resultdetection targets is the initial detection target detected by thesensor.

Optionally, the method further includes: calculating a spatial matchingconfidence of the detection result in the current detection period basedon the number of successful matches among the spatial positions of allthe result detection targets in the current detection period, whereinthe target detection information of the detection result furthercomprises the spatial matching confidence of the detection result in thecurrent detection period.

Optionally, generating target detection information of the detectionresult includes: generating the target detection information of thedetection result in a case that the spatial matching confidence of thedetection result in the current detection period is greater than apreset spatial confidence threshold.

Optionally, the method further includes: determining a time matchingconfidence of the detection result by performing a weighting operationon spatial matching confidences of the detection result in a pluralityof recent detection periods, wherein the target detection information ofthe detection result further comprises the time matching confidence ofthe detection result.

Optionally, generating target detection information of the detectionresult includes: generating the target detection information of thedetection result in a case that the time matching confidence of thedetection result is greater than a preset time confidence threshold.

Optionally, it is determined that spatial positions of two of theinitial detection targets to be matched are matched with each other, ina case that a Euclidean distance between the spatial positions of thetwo of the initial detection targets to be matched is within a presetdistance threshold.

Optionally, the method further includes:

determining a screening range in the plane coordinate system based on acurrent speed of a vehicle; and

determining the initial detection targets to be matched based on thescreening range, wherein spatial positions of the initial detectiontargets to be matched are within the screening range.

Optionally, the screening range is a range of all spatial positions ableto be passed by the vehicle in a case that a turning radius exceeds acurrent radius threshold and a path does not exceed a current paththreshold, wherein the current radius threshold is determined based onthe current speed of the vehicle and a lateral acceleration threshold,and the current path threshold is determined based on the current speedof the vehicle and a preset time threshold.

Optionally, the spatial matching confidence of the detection result inthe current detection period is a ratio of the number of successfulmatches corresponding to the detection result to the total number ofmatches, wherein the number of successful matches corresponding to thedetection result is the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod, and the total number of matches is the number of matches amongall the initial detection targets to be matched in the current detectionperiod.

Optionally, determining the time matching confidence of the detectionresult by performing the weighting operation on the spatial matchingconfidences of the detection result in the plurality of recent detectionperiods comprises:

adding results obtained by multiplying a spatial matching confidence ineach of the plurality of recent detection periods by a weightingcoefficient corresponding to the detection period, to obtain the timematching confidence of the detection result, wherein the closer thedetection period is to a current time instant, the greater the weightingcoefficient corresponding to the detection period is.

Optionally, the weighting coefficient corresponding to each of thedetection periods is a normalized weighting coefficient.

Optionally, the multiple different types of sensors include a camera, aradar and/or a laser radar. A dimension corresponding to the camera isan image characteristic of the detected target object, a dimensioncorresponding to the radar is a relative speed of the detected targetobject with respect to the vehicle, and a dimension corresponding to thelaser radar is a profile of the detected target object.

In another aspect, it is provided an apparatus for generating targetdetection information, including:

a first determining unit configured to determine, in a unified planecoordinate system, spatial positions of initial detection targetsdetected by a plurality of different types of sensors in a currentdetection period;

a second determining unit configured to match spatial positions ofinitial detection targets to be matched detected by every two of theplurality of different types of sensors in the current detection period,and determine the initial detection targets under a detection result asresult detection targets, wherein spatial positions of any two of theresult detection targets under the detection result are matched witheach other; and

a generating unit configured to generate target detection information ofthe detection result, wherein the target detection information of thedetection result comprises target detection information on each of theresult detection targets, which is collected by the sensor detecting theresult detection target in a dimension corresponding to the sensor, andeach of the result detection targets is the initial detection targetdetected by the sensor.

Optionally, the apparatus may further include a calculating unit,configured to calculate a spatial matching confidence of the detectionresult in the current detection period based on the number of successfulmatches among the spatial positions of all the result detection targetsin the current detection period. The target detection information of thedetection result further includes the spatial matching confidence of thedetection result in the current detection period.

Optionally, the generating unit is configured to generate targetdetection information of the detection result in a case that the spatialmatching confidence of the detection result in the current detectionperiod is greater than a preset spatial confidence threshold.

Optionally, the apparatus may further include a third determining unit,configured to determine a time matching confidence of the detectionresult by performing a weighting operation on spatial matchingconfidences of the detection result in multiple recent detectionperiods.

The target detection information of the detection result furtherincludes the time matching confidence of the detection result.

Optionally, the generating unit is configured to generate targetdetection information of the detection result in a case that the timematching confidence of the detection result is greater than a presettime confidence threshold.

Optionally, in a case that a Euclidean distance between spatialpositions of two initial detection targets to be matched is within apreset distance threshold, it is determined that the spatial positionsof the two initial detection targets to be matched are matched with eachother.

Optionally, the apparatus may further include: a fourth determining unitconfigured to determine a screening range in the plane coordinate systembased on a current speed of a vehicle; and a fifth determining unitconfigured to determine initial detection targets to be matched based onthe screening range. Spatial positions of the initial detection targetsto be matched are located within the screening range.

Optionally, the screening range is a range of all possible spatialpositions passed by the vehicle in a case that a turning radius of thevehicle does not exceed a current radius threshold and a path of thevehicle does not exceed a current path threshold. The current radiusthreshold is determined based on the current speed of the vehicle and alateral acceleration threshold, and the current path threshold isdetermined based on the current speed of the vehicle and a preset timethreshold.

Optionally, the spatial matching confidence of the detection result inthe current detection period may be a ratio of the number of successfulmatches corresponding to the detection result to the total number ofmatches, wherein the number of successful matches corresponding to thedetection result is the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod, and the total number of matches is the number of matches amongall the initial detection targets to be matched in the current detectionperiod.

Optionally, the third determining unit is configured to add resultsobtained by multiplying a spatial matching confidence in each of theplurality of recent detection periods by a weighting coefficientcorresponding to the detection period, to obtain the time matchingconfidence of the detection result. The closer the detection period isto a current time instant, the greater the weighting coefficientcorresponding to the detection period is

Optionally, the weighting coefficient corresponding to each of thedetection periods may be a normalized weighting coefficient.

Optionally, the multiple different types of sensors include a camera, aradar and/or a laser radar. A dimension corresponding to the camera isan image characteristic of the detected target object, a dimensioncorresponding to the radar is a relative speed of the detected targetobject with respect to the vehicle, and a dimension corresponding to thelaser radar is a profile of the detected target object.

In another aspect, it is provided a device for generating targetdetection information, comprising a processor, a storage, acommunication interface and a bus system, wherein

the bus system is configured to couple the processor, the storage andthe communication interface together;

the communication interface is configured to implement communicationconnection between the device and at least one other device;

the storage is configured to storage instructions; and

the processor is configured to read the instructions stored in thestorage, to perform steps of:

determining, in a unified plane coordinate system, spatial positions ofinitial detection targets detected by a plurality of different types ofsensors in a current detection period;

matching spatial positions of initial detection targets to be matcheddetected by every two of the plurality of different types of sensors inthe current detection period, and determining the initial detectiontargets under a detection result as result detection targets, whereinspatial positions of any two of the result detection targets under thedetection result are matched with each other; and

generating target detection information of the detection result, whereinthe target detection information of the detection result comprisestarget detection information on each of the result detection targets,which is collected by the sensor detecting the result detection targetin a dimension corresponding to the sensor, and each of the resultdetection targets is the initial detection target detected by thesensor.

Optionally, the processor is further configured to calculate a spatialmatching confidence of the detection result in the current detectionperiod based on the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod. The target detection information of the detection result furtherincludes the spatial matching confidence of the detection result in thecurrent detection period.

Optionally, in order to generate the target detection information of thedetection result, the processor is further configured to generate targetdetection information of the detection result in a case that the spatialmatching confidence of the detection result in the current detectionperiod is greater than a preset spatial confidence threshold.

Optionally, the processor is further configured to determine a timematching confidence of the detection result by performing a weightingoperation on spatial matching confidences of the detection result inmultiple recent detection periods. The target detection information ofthe detection result further includes the time matching confidence ofthe detection result.

Optionally, in order to generate the target detection information of thedetection result, the processor is further configured to generate thetarget detection information of the detection result in a case that thetime matching confidence of the detection result is greater than apreset time confidence threshold.

Optionally, in a case that a Euclidean distance between spatialpositions of two initial detection targets to be matched is within apreset distance threshold, it is determined that the spatial positionsof the two initial detection targets to be matched are matched with eachother.

Optionally, the processor is further configured to: determine ascreening range in the plane coordinate system based on a current speedof a vehicle; and determine the initial detection targets to be matchedbased on the screening range. Spatial positions of the initial detectiontargets to be matched are located within the screening range.

Optionally, the screening range is a range of all possible spatialpositions passed by the vehicle in a case that a turning radius of thevehicle does not exceed a current radius threshold and a path of thevehicle does not exceed a current path threshold. The current radiusthreshold is determined based on the current speed of the vehicle and alateral acceleration threshold, and the current path threshold isdetermined based on the current speed of the vehicle and a preset timethreshold.

Optionally, the spatial matching confidence of the detection result inthe current detection period may be a ratio of the number of successfulmatches corresponding to the detection result to the total number ofmatches. The number of successful matches corresponding to the detectionresult is the number of successful matches among the spatial positionsof all the result detection targets in the current detection period, andthe total number of matches is the number of matches among all theinitial detection targets to be matched in the current detection period.

Optionally, in order to determine the time matching confidence of thedetection result, the processor is further configured to obtain the timematching confidence of the detection result by multiplying the spatialmatching confidence in each of the multiple recent detection periodswith a weighting coefficient corresponding to the detection period andadding the obtained products together. The closer the detection periodis to a current time instant, the greater the weighting coefficientcorresponding to the detection period is.

Optionally, the weighting coefficient corresponding to each of thedetection periods is a normalized weighting coefficient.

Optionally, the multiple different types of sensors include a camera, aradar and/or a laser radar. A dimension corresponding to the camera isan image characteristic of the detected target object, a dimensioncorresponding to the radar is a relative speed of the detected targetobject with respect to the vehicle, and a dimension corresponding to thelaser radar is a profile of the detected target object.

According to embodiments of the present disclosure, target objectsaround the vehicle are detected by multiple different types of sensors,and the detection targets representing a same target object, which aredetected by the different types of sensors, are determined by spatialposition matching. A spatial matching confidence is calculated, and atime matching confidence is calculated by tracing the detection targetsover time. With taking the target object as a detection result, thetarget detection information generated for the detection result includesa spatial matching confidence of the detection result in the currentdetection period, a time matching confidence of the detection result,and target detection information on each of the detection targetsrepresenting the detection result, where the target detectioninformation on the detection target is collected by the sensor detectingthe detection target in a dimension corresponding to the sensor. It canbe seen that, on one hand, the possibility that the detection targetsdetected by different types of sensors presents a same target object canbe determined according to the spatial matching confidence and the timematching confidence, and false detection or missing detection for thetarget object is greatly reduced in view of different advantages ofdifferent sensors. On the other hand, according to the dimensions of thetarget detection information that can be accurately collected by thedifferent types of sensors, target detection information accuratelycollected by different types of sensors in different dimensions is fusedto obtain target detection information on the same target object,thereby providing more accurate and completer target detectioninformation on the target object.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to clearly illustrate the technical solutions in theembodiments of the present disclosure, in the following, drawings usedin the description of the embodiments will be introduced simply.Apparently, the drawings in the following description are only someembodiments of the present disclosure. Other drawings can also beobtained by those skilled in the art according to the drawings.

FIG. 1 is a schematic diagram of a system framework related to anapplication scenario according to an embodiment of the presentdisclosure;

FIG. 2 is a schematic flowchart of a method for generating targetdetection information according to an embodiment of the presentdisclosure;

FIG. 3 is a schematic diagram of a plane coordinate system according toan embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a screening range according to anembodiment of the present disclosure;

FIG. 5 is a schematic diagram of a turning radius of a vehicle when thevehicle is in the maximum turning angle according to an embodiment ofthe present disclosure;

FIG. 6 is a schematic diagram of spatial positions of initial detectiontargets detected by different sensors in a unified plane coordinatesystem according to an embodiment of the present disclosure;

FIG. 7 is a schematic flowchart of a method for generating targetdetection information according to an embodiment of the presentdisclosure;

FIG. 8 is a schematic structural diagram of an apparatus for generatingtarget detection information according to an embodiment of the presentdisclosure; and

FIG. 9 is a schematic structural diagram of a device for generatingtarget detection information according to an embodiment of the presentdisclosure.

DETAILED DESCRIPTION OF THE EMBODIMENTS

In order to make those skilled in the art better understand the solutionof the present disclosure, hereinafter, the technical solutions in theembodiments of the present disclosure will be described clearly andcompletely in conjunction with the drawings in the embodiments of thepresent disclosure. Apparently, the described embodiments are only apart of the embodiments of the present disclosure, rather than all theembodiments. All the other embodiments obtained by those skilled in theart based on the embodiments of the present disclosure without creativework will fall within the protection scope of the present disclosure.

The invertor, through research, found that different types of sensorsdetect a target object according to different detection mechanisms, andthus the different types of sensors have different detection advantagesand disadvantages. For example, a camera sensor detects a target objectby acquiring visual imaging through a camera, and the viewing angle canreaches a range from −90 degrees to +90 degrees. For another example, aradar sensor detects a target object by comparing a transmittedelectromagnetic wave with a received electromagnetic wave, thelong-distance detection can reach 200 meters and a range from −10degrees to +10 degrees, and the middle-distance detection can reach 50meters and a range from −45 degrees to +45 degrees. For another example,a laser radar sensor detects a target object by scanning the targetobject through laser beam, and the detection can reach 200 meter and arange from −45 degrees to +45 degrees under good conditions.Conventionally, the target objects around the vehicle are detected by asingle type of sensor, and the single type of sensor certainly has somedetection disadvantages when detecting the target objects around thevehicle. For example, target detection information in some dimensionsmay cannot be collected by a single type of sensor or the collectedtarget detection information in some dimensions may not be accurate, oreven in some cases the target object cannot be detected. Therefore, byusing a single type of sensor to detect target objects, false detectionor missing detection may occur, and accurate and complete targetdetection information in multiple dimensions cannot be obtained.

In order to solve the problem, in the embodiments of the presentdisclosure, target objects around the vehicle are detected by multipledifferent types of sensors, and the detection targets representing asame target object, which are detected by the different types ofsensors, are determined by spatial position matching. With taking thetarget object as a detection result, the target detection informationgenerated for the detection result includes a spatial matchingconfidence of the detection result in the current detection period, atime matching confidence of the detection result, and target detectioninformation on each of the detection targets representing the detectionresult, where the target detection information on the detection targetis collected by the sensor detecting the detection target in a dimensioncorresponding to the sensor. It can be seen that, on one hand, thepossibility that the detection targets detected by different types ofsensors presents a same target object can be determined according to thespatial matching confidence and the time matching confidence, and falsedetection or missing detection for the target object is greatly reducedin view of different advantages of different sensors. On the other hand,according to the dimensions of the target detection information that canbe accurately collected by the different types of sensors, targetdetection information accurately collected by different types of sensorsin different dimensions is fused to obtain target detection informationon the same target object, thereby providing more accurate and completertarget detection information on the target object.

FIG. 1 illustrates a scenario according to an embodiment of the presentdisclosure. The scenario includes a camera sensor 101, a radar sensor102, a laser radio sensor 103 and a processor 104. The camera sensor 101can interact with the processor 104, the radar sensor 102 can interactwith the processor 104, and the laser radio sensor 103 can interact withthe processor 104. The processor 104 determines, in a unified planecoordinate system, spatial positions of initial detection targetsdetected by each of the camera sensor 101, the radar sensor 102 and thelaser radar sensor 103 in a current detection period. The processor 104matches spatial positions of the initial detection targets to be matchedcollected by the camera sensor 101 and the radar sensor 102, spatialpositions of the initial detection targets to be matched collected bythe radar sensor 102 and the laser radar sensor 103 and spatialpositions of the initial detection targets to be matched collected bythe camera sensor 101 and the laser radar sensor 103 in the currentdetection period, and determines initial detection targets under adetection result as result detection targets, where spatial positions ofany two result detection targets under the detection result are matchedwith each other. The processor 104 further calculates a spatial matchingconfidence of the detection result in the current detection period basedon the number of successful matches among the spatial positions of theresult detection targets in the current detection period. The processor104 further determines a time matching confidence of the detectionresult by performing a weighting operation on spatial matchingconfidences of the detection result in multiple recent detectionperiods. The processor 104 generates target detection information of thedetection result. The target detection information of the detectionresult includes the spatial matching confidence of the detection resultin the current detection period, a time matching confidence of thedetection result, and target detection information on each of the resultdetection targets, which is collected by the sensor detecting the resultdetection target in a dimension corresponding to the sensor. The resultdetection targets are the initial detection targets detected by thesensors.

The actions according to the embodiment of the present disclosure areexecuted by the processor 104 in the above scenario, however, theexecutive subject in the present disclosure is not limited thereto, aslong as the actions according to the embodiment of the presentdisclosure are performed.

It should be noted that the above scenario is only an example of thescenarios of the present disclosure, and the present disclosure is notlimited to the above scenario.

A method, an apparatus and a device for generating target detectioninformation according to embodiments of the present disclosure aredescribed in detail below in conjunction with the drawings.

Exemplary Methods

FIG. 2 illustrates a schematic flowchart of a method for generatingtarget detection information according to an embodiment of the presentdisclosure. The method may include steps 201 to 203.

In step 201, spatial positions of initial detection targets detected bymultiple different types of sensors in a current detection period aredetermined in a unified plane coordinate system.

The spatial positions of the initial detection targets detected bydifferent sensors are identified in independent coordinate systems ofthe different sensors, respectively, and the independent coordinatesystems of the different sensors are usually different. In order todetermine initial detection targets representing a same target object byanalyzing relations among the spatial positions of the initial detectiontargets detected by the different sensors, a unified plane coordinatesystem is created and the spatial positions of the initial detectiontargets detected by the sensors are transformed into the unified planecoordinate system. For example, the unified plane coordinate system mayadopt the coordinate system shown in FIG. 3. In the coordinate system inFIG. 3, a coordinate plane of the coordinate system example is definedby a roll axis and a pitch axis of the vehicle, an origin O of thecoordinate system denotes a scanning midpoint of the sensor, a positivedirection of an X-axis of the coordinate system is a forward directionof the vehicle, and a positive direction of a Y-axis of the coordinatesystem is a right direction perpendicular to the forward direction ofthe vehicle.

The sensor commonly used for detecting target objects around the vehiclemay be a camera, a radar, a laser radar and the like. In the embodiment,multiple different types of sensors may include for example a camera, aradar and/or a laser radar.

In step 202, spatial positions between the initial detection targets tobe matched detected by every two different sensors in a currentdetection period is matched, and the initial detection targets under adetection result are determined as result detection targets, whereinspatial positions of any two of the result detection targets under thedetection result are matched with each other.

In the embodiment, one detection result corresponds to one target objectaround the vehicle. The initial detection targets under a detectionresult may be understood as detection targets obtained by detecting asame target object by different types of sensors. The spatial positionsof the initial detection targets which are obtained by detecting a sametarget by the different types of sensors, may be slightly different inthe unified plane coordinate system. If spatial positions of initialdetection targets detected by two different sensors are close to eachother, the spatial positions of the two initial detection targets can beregarded to be matched with each other, and the two initial detectiontargets can be regarded as targets obtained by detecting a same targetobject by different sensors. That is, the two initial detection targetsrepresent a same target object, and are under a same detection result.Therefore, in the step 202, for all initial detection targets to bematched, the spatial position matching is performed between the initialdetection targets to be matched detected by every two different types ofsensors. If spatial positions of the two initial detection targets to bematched are matched with each other, it is determined that the twoinitial detection targets to be matched correspond to a same detectionresult. In this way, initial detection targets under a same detectionresult can be determined according to results of matching spatialpositions of all initial detection targets to be matched.

For example, a target object is detected by three types of sensors,which are a camera, a radar and a laser radar. Initial detection targetsdetected by the camera include A and B, initial detection targetsdetected by the radar include C and D, and initial detection targetsdetected by the laser radar include E and F; and the initial detectiontargets to be matched include A, B, C, D, E and F. In matching spatialpositions between the initial detection targets to be matched detectedby different sensors, spatial position matching is performed between Aand C, spatial position matching is performed between A and D, spatialposition matching is performed between A and E, spatial positionmatching is performed between A and F, spatial position matching isperformed between B and C, spatial position matching is performedbetween B and D, spatial position matching is performed between B and E,spatial position matching is performed between B and F, spatial positionmatching is performed between C and E, spatial position matching isperformed between C and F, spatial position matching is performedbetween D and E, and spatial position matching is performed between Dand F. In a case that the spatial position of A and the spatial positionof C are matched with each other, the spatial position of C and thespatial position of F are matched with each other, and the spatialposition of A and the spatial position of F are matched with each other,it is determined that A, C and F are initial detection targets in a samedetection result representing a same target object, and A, C and F aredetermined as result detection targets in the detection result. That is,the spatial position of each initial detection target to be matcheddetected by each of the plurality of different types of sensors ismatched with the spatial position of each initial detection target to bematched detected by each of others of the plurality of different typesof sensors, to determine initial detection target under a same detectionresult.

For example, the distance between spatial positions of different initialdetection targets may be indicated by a Euclidean distance. Therefore,the spatial positions of the two initial detection targets to be matchedmay be matched according to the Euclidean distance between the twoinitial detection targets in the unified plane coordinate system. If theEuclidean distance between the spatial positions of the two initialdetection targets is small, the two initial detection targets isregarded as representing a same target object, and it can be determinedthat the two initial detection targets are initial detection targetsunder a same detection result. That is, it is determined that thespatial positions of the two initial detection targets to be matched arematched with each other if the Euclidean distance between the spatialpositions of the two initial detection targets is within a presetdistance threshold.

For example, as shown in FIG. 6, A (x_(cn), y_(cn)) denotes an initialdetection target detected by the camera, B (x_(rm), y_(rm)) denotes aninitial detection target detected by the radar, and C (x_(lm), y_(lm))denotes an initial detection target detected by the laser radar. AEuclidean distance between spatial positions of the two initialdetection targets A and B to be matched may be calculated according to aformula as follows.d _(m)=√{square root over ((x _(rm) −x _(cn))²+(y _(rm) −y _(cn))²)}

where d_(m) denotes a Euclidean distance between spatial positions of Aand B, x_(rm) denotes an x-coordinate of the spatial position of theinitial detection target detected by the radar, x_(cn) denotes anx-coordinate of the spatial position of the initial detection targetdetected by the camera, y_(rm) denotes a y-coordinate of the spatialposition of the initial detection target detected by the radar, andy_(cn) denotes a y-coordinate of the spatial position of the initialdetection target detected by the camera. If d_(m) is less than a presetdistance threshold D, it is determined that the spatial position of theinitial detection target A detected by the radar and the spatialposition of the initial detection target B detected by the camera arematched with each other. The preset distance threshold D should be lessthan the minimum distance between different target objects, to preventsuccessful match between spatial positions of initial detection targetscorresponding to different target objects. If the spatial positions of Aand B are matched with each other, the spatial positions of B and C arematched with each other, and the spatial positions of A and C arematched with each other, it is determined that A, B and C represent asame target object, that is, A, B and C are initial detection targetsunder a same detection result.

In addition, there are usually a large number of target objects that aredetected by the sensors, which results in a large amount of processingfor spatial matching. In some embodiments of the present disclosure, inorder to reduce the amount of processing for spatial matching, ascreening range is formed based on positions where the vehicle canarrive within a reaction time of a driver, and spatial matching isperformed between only initial detection targets detected by differenttypes of sensors within the screening range. Before step S202, themethod may further include: determining a screening range in the unifiedplane coordinate system based on the current speed of the vehicle; anddetermining initial detection targets whose spatial positions are withinthe screening range as initial detection targets to be matched. Thespatial positions of the initial detection targets to be matched arelocated within the screening range.

In an implementation, the screening range may be determined according tothe minimum turning radius of the vehicle in the current position andthe farthest path within the reaction time of the driver. In one aspect,considering that the vehicle has a lateral acceleration when turning atthe current speed, the lateral acceleration of the vehicle may belimited to a value within a lateral acceleration threshold, to ensuredriving safety and traveling comfort. In this case, the minimum turningradius of the vehicle at the current position can be obtained based onthe lateral acceleration threshold and the current speed of the vehicle,and the minimum turning radius may be used as the current radiusthreshold. If the lateral acceleration of the vehicle is not greaterthan the lateral acceleration threshold, the turning radius of thevehicle is not less than the current radius threshold, therefore theturning radius corresponding to the screening range is not less than thecurrent radius threshold. In another aspect, considering that the driverhas a reaction time when driving the vehicle, the target objects to bematched are mainly target objects which may be collided by the vehiclein the reaction time of the driver. Therefore, a preset time thresholdis used to represent the reaction time of the driver, and the farthestpath of the vehicle at the current position within the reaction time ofthe driver can be obtained according to the preset time threshold andthe current speed of the vehicle. The farthest path may be used as thecurrent path threshold. If the reaction time is not greater than thepreset time threshold, the driving path of the vehicle is not greaterthan the current path threshold, therefore the path corresponding to thescreening range is not greater than the current path threshold. Inconjunction with the two aspects above, the screening range may be arange of all possible spatial positions passed by the vehicle in a casethat the turning radius exceeds the current radius threshold and thepath does not exceed the current path threshold. The current radiusthreshold is determined based on the current speed of the vehicle andthe lateral acceleration threshold, and the current path threshold isdetermined based on the current speed of the vehicle and the preset timethreshold. For example, as an example of the screening range shown inFIG. 4, the screening range D is an area surrounded by two curves L₁ andL₂ and a straight line L₃. Curvature radiuses of the two curves are thecurrent radius threshold, and the air line distance between the straightline L₃ and the current position of the vehicle is the current paththreshold.

The current radius threshold and the current path threshold may becalculated according to formulas as follows.

${{Radius} = \frac{V_{x}^{2}}{A_{y}}};\mspace{14mu}{d = {V_{x} \times t_{reaction}}}$

where Radius denotes the current radius threshold, V, denotes thecurrent speed of the vehicle, A_(y) denotes the lateral accelerationthreshold, d denotes the current path threshold, and t_(reaction)denotes the preset time threshold.

In addition, the current turning radius may be determined based on amaximum turning angle of the vehicle. As shown in FIG. 5, δ_(max)denotes a maximum turning angle of turning system of the vehicle, L is awheelbase, Radius_(min) may be a minimum turning radius of the vehicle,therefore

${Radius}_{\min} = \frac{L}{\sin\left( \delta_{\max} \right)}$

In step 203, target detection information of the detection result isgenerated. The target detection information of the detection resultincludes target detection information on each of the result detectiontargets, which is collected by the sensor detecting the result detectiontarget in a dimension corresponding to the sensor. The result detectiontargets are the initial detection targets detected by the sensors.

Commonly used on-vehicle sensors for sensing ambient environment includea camera, a radar, a laser radar and the like. The camera can depict,for example, appearance and shape of the detected target by visualimaging. The radar can obtain an orientation of the detected target anda relative speed of the detected target with respect to the vehicle bycomparing characteristics of transmitted electromagnetic wave withcharacteristics of received electromagnetic wave. The laser radar canobtain a profile of the detected target by laser beam scanning. In theembodiment, the multiple different types of sensors may include forexample the camera, the radar and/or the laser radar. A dimensioncorresponding to the camera may be an image characteristic of thedetected target, a dimension corresponding to the radar may be arelative speed of the detected target with respect to the vehicle, and adimension corresponding to the laser radar may be a profile of thedetected target. As an example, in a case that a same target object isdetected by the camera, the radar or the laser radar when the vehicle isrunning, the target detection information of the detection resultrepresenting the target object may include an image characteristic (forexample, a geometric characteristic) of the target object detected bythe camera, a relative speed of the target object with respect to thevehicle detected by the radar, and a profile of the target objectdetected by the laser radar.

In some embodiments, in order to determine whether all result detectiontargets under the detection result can represent a same target objectbased on the target detection information of the detection result, thetarget detection information of the detection result may further includea spatial matching confidence of the detection result in the currentdetection period. In this case, before the step S203, the methodaccording to the embodiment may further include: calculating a spatialmatching confidence of the detection result in the current detectionperiod based on the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod.

The spatial matching confidence of the detection result in the currentdetection period refers to a possibility that the initial detectiontargets under the detection result in the current detection periodrepresents a same target object from a spatial position perspective. Thespatial matching confidence of the detection result in the currentdetection period may be for example a ratio of the number of matchescorresponding to the detection result to the total number of matches.The number of matches corresponding to the detection result is thenumber of successful matches among the spatial positions of all theresult detection targets in the current detection period, and the totalnumber of matches is the number of matches between all initial detectiontargets to be matched in the current detection period, i.e., includingall successful matches and unsuccessful matches.

For example, assumed that two sensors which are a camera and a radar areused to detect a target object. Initial detection targets detected bythe camera include A and B, and initial detection targets detected bythe radar include C and D, then initial detection targets to be matchedmay include A, B, C and D. Since spatial position matching is performedbetween initial detection targets to be matched detected by differentsensors, spatial position matching is performed between A and C, spatialposition matching is performed between A and D, spatial positionmatching is performed between B and C, and spatial position matching isperformed between B and D. In this case, the number of matches among theinitial detection targets to be matched is 4, that is, the total numberof matches is 4. Assumed that the spatial position of A is matched withthe spatial position of C, the spatial position of A is not matched withthe spatial position of D, the spatial position of B is not matched withthe spatial position of C, and the spatial position of B is not matchedwith the spatial position of D, then in this case, A and C is resultdetection targets in a same detection result. Therefore, the number ofsuccessful matches among the spatial positions of all the resultdetection targets is 1, that is, the number of matches corresponding tothe detection result is 1.

In some embodiments, target detection information including informationdetected by different sensors is generated only for a detection resulthaving a high spatial matching confidence. In this case, step 203 mayinclude: generating target detection information of a detection resultin a case that the spatial matching confidence of the detection resultin the current detection period is greater than a preset spatialconfidence threshold.

In some embodiments, in order to determine whether detection results indifferent detection periods can indicate a same target object based onthe target detection information of the detection result, the targetdetection information of the detection result may further include a timematching confidence of the detection result. In this case, before step203, the method according to the embodiment may further include:determining a time matching confidence of the detection result byperforming a weighting operation on spatial matching confidences of thedetection result in multiple recent detection periods.

By using different sensors to detect target objects in differentdetection periods, detected initial detection targets to be matched maybe different, and spatial matching confidences of the detection resultin different detection periods may be different. In order to determinewhether the detection result in different detection periods represent asame target object, the spatial matching confidences of the detectionresult in multiple different detection periods may be traced, to obtaina time matching confidence of the detection result. The time matchingconfidence of the detection result refers to a possibility that thedetection result in multiple different detection periods represents asame target object from time perspective.

In some embodiments, target detection information including informationdetected by different sensors is generated only for a detection resulthaving a high time matching confidence. In this case, step 203 mayfurther include: generating the target detection information of thedetection result in a case that the time matching confidence of thedetection result is greater than a preset time confidence threshold.

In some embodiments, the time matching confidence of the detectionresult may be determined by multiplying a spatial matching confidence ineach of the multiple recent detection periods with a weightingcoefficient corresponding to the detection period and adding theobtained products together. The closer the detection period is to acurrent time instant, the greater the weighting coefficientcorresponding to the detection period is. In an implementation, theweighting coefficient corresponding to each detection period may be anormalized weighting coefficient, that is, the sum of weightingcoefficients corresponding to all the multiple recent detection periodsis equal to 1.

In an implementation, the time matching confidence may be calculatedaccording to a formula as follows.

$P_{tracking} = {{\frac{m}{2\; m}{P_{L}(c)}} + {\frac{m - 1}{2\; m}{P_{L}\left( {c - 1} \right)}} + \ldots + {\frac{m - \left( {m - 1} \right)}{2\; m}{P_{L}\left( {c - \left( {m - 1} \right)} \right)}}}$

where P_(tracting) denotes the time matching confidence; c, c−1 . . .c−(m−1) denote a current detection period, a first detection periodbefore the current detection period . . . a (m−1)th detection periodbefore the current detection period, respectively, which are m recentdetection periods; P_(L)(c), P_(L)(c−1) . . . P_(L)(c−(m−1)) denotespatial matching confidences of the

$\frac{m}{2\; m},{\frac{m - 1}{2\; m}\mspace{14mu}\ldots\mspace{14mu}\frac{m - \left( {m - 1} \right)}{2\; m}}$detection result in the m recent detection periods, respectively, m is apositive integer, denote weighting coefficients corresponding to the mrecent detection periods, respectively.

According to the embodiments of the present disclosure, target objectsaround the vehicle are detected by multiple different types of sensors,and the detection targets representing a same target object, which aredetected by the different types of sensors, are determined by spatialposition matching. With taking the target object as a detection result,the target detection information generated for the detection resultincludes a spatial matching confidence of the detection result in thecurrent detection period, a time matching confidence of the detectionresult, and target detection information on each of the detectiontargets representing the detection result, where the target detectioninformation on the detection target is collected by the sensor detectingthe detection target in a dimension corresponding to the sensor. It canbe seen that, on one hand, the possibility that the detection targetsdetected by different types of sensors presents a same target object canbe determined according to the spatial matching confidence and the timematching confidence, and false detection or missing detection for thetarget object is greatly reduced in view of different advantages ofdifferent sensors. On the other hand, according to the dimensions of thetarget detection information that can be accurately collected by thedifferent types of sensors, target detection information accuratelycollected by different types of sensors in different dimensions is fusedto obtain target detection information on the same target object,thereby providing more accurate and completer target detectioninformation on the target object.

FIG. 7 is a schematic flowchart of another method for generating targetdetection information according to an embodiment of the presentdisclosure. In the embodiment, the method may include step 701 to step707.

In step 701, a unified plane coordinate system is formed, and ascreening range is determined in the plane coordinate system based on acurrent speed of a vehicle.

In step 702, spatial positions of initial detection targets detected bymultiple different types of sensors in a current detection period aredetermined in the unified plane coordinate system.

In step 703, initial detection targets to be matched are determinedbased on the screening range. Spatial positions of the initial detectiontargets to be matched are located within the screening range.

In step 704, spatial positions of initial detection targets to bematched detected by every two different sensors in the current detectionperiod are marched, and initial detection targets under a detectionresult are determined as result detection targets. Spatial positions ofany two result detection targets under the detection result are matchedwith each other.

In step 705, a spatial matching confidence of the detection result inthe current detection period is calculated based on the number ofsuccessful matches among spatial positions of all the result detectiontargets in the current detection period.

In step 706, a time matching confidence of the detection result isdetermined by performing a weighting operation on the spatial matchingconfidences of the detection result in multiple recent detectionperiods.

In step 707, target detection information of the detection result isgenerated. The target detection information of the detection resultincludes the spatial matching confidence of the detection result in thecurrent detection period, the time matching confidence of the detectionresult, and target detection information on each of the result detectiontargets, which is detected by the sensor detecting the result detectiontarget in a dimension corresponding to the sensor. Each of the resultdetection targets is the initial detection target detected by thesensor.

According to the embodiments of the present disclosure, target objectsaround the vehicle are detected by multiple different types of sensors,and the detection targets representing a same target object, which aredetected by the different types of sensors, are determined by spatialposition matching. With taking the target object as a detection result,the target detection information generated for the detection resultincludes a spatial matching confidence of the detection result in thecurrent detection period, a time matching confidence of the detectionresult, and target detection information on each of the detectiontargets representing the detection result, where the target detectioninformation on the detection target is collected by the sensor detectingthe detection target in a dimension corresponding to the sensor. It canbe seen that, on one hand, the possibility that the detection targetsdetected by different types of sensors presents a same target object canbe determined according to the spatial matching confidence and the timematching confidence, and false detection or missing detection for thetarget object is greatly reduced in view of different advantages ofdifferent sensors. On the other hand, according to the dimensions of thetarget detection information that can be accurately collected by thedifferent types of sensors, target detection information accuratelycollected by different types of sensors in different dimensions is fusedto obtain target detection information on the same target object,thereby providing more accurate and completer target detectioninformation on the target object.

Exemplary Device

FIG. 8 is a schematic structural diagram of an apparatus for generatingtarget detection information according to an embodiment of the presentdisclosure. In the embodiment, the apparatus may include a firstdetermining unit 801, a second determining unit 802 and a generatingunit 803.

The first determining unit 801 is configured to determine, in a unifiedplane coordinate system, spatial positions of initial detection targetsdetected by a plurality of different types of sensors in a currentdetection period.

The second determining unit 802 is configured to match spatial positionsof initial detection targets to be matched detected by every two of theplurality of different types of sensors in the current detection period,and determine the initial detection targets under a detection result asresult detection targets, wherein spatial positions of any two of theresult detection targets under the detection result are matched witheach other.

The generating unit 803 is configured to generate target detectioninformation of the detection result, wherein the target detectioninformation of the detection result comprises target detectioninformation on each of the result detection targets, which is collectedby the sensor detecting the result detection target in a dimensioncorresponding to the sensor, and each of the result detection targets isthe initial detection target detected by the sensor.

Optionally, the apparatus may further include a calculating unit.

The calculating unit is configured to calculate a spatial matchingconfidence of the detection result in the current detection period basedon the number of successful matches among the spatial positions of allthe result detection targets in the current detection period.

The target detection information of the detection result furtherincludes the spatial matching confidence of the detection result in thecurrent detection period.

Optionally, the generating unit 803 is configured to generate targetdetection information of the detection result in a case that the spatialmatching confidence of the detection result in the current detectionperiod is greater than a preset spatial confidence threshold.

Optionally, the apparatus may further include a third determining unit,configured to determine a time matching confidence of the detectionresult by performing a weighting operation on spatial matchingconfidences of the detection result in multiple recent detectionperiods.

The target detection information of the detection result furtherincludes the time matching confidence of the detection result.

Optionally, the generating unit 803 is configured to generate targetdetection information of the detection result in a case that the timematching confidence of the detection result is greater than a presettime confidence threshold.

Optionally, in a case that a Euclidean distance between spatialpositions of two initial detection targets to be matched is within apreset distance threshold, it is determined that the spatial positionsof the two initial detection targets to be matched are matched with eachother.

Optionally, the apparatus may further include: a fourth determining unitconfigured to determine a screening range in the plane coordinate systembased on a current speed of vehicle; and a fifth determining unitconfigured to determine initial detection targets to be matched based onthe screening range. Spatial positions of the initial detection targetsto be matched are located within the screening range.

Optionally, the screening range is a range of all possible spatialpositions passed by the vehicle in a case that a turning radius of thevehicle exceeds a current radius threshold and a path of the vehicledoes not exceed a current path threshold. The current radius thresholdis determined based on the current speed of the vehicle and a lateralacceleration threshold, and the current path threshold is determinedbased on the current speed of the vehicle and a preset time threshold.

Optionally, the spatial matching confidence of the detection result inthe current detection period may be a ratio of the number of successfulmatches corresponding to the detection result to the total number ofmatches, wherein the number of successful matches corresponding to thedetection result is the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod, and the total number of matches is the number of matches amongall the initial detection targets to be matched in the current detectionperiod.

Optionally, the third determining unit is configured to add resultsobtained by multiplying a spatial matching confidence in each of theplurality of recent detection periods by a weighting coefficientcorresponding to the detection period, to obtain the time matchingconfidence of the detection result. The closer the detection period isto a current time instant, the greater the weighting coefficientcorresponding to the detection period is

Optionally, the weighting coefficient corresponding to each of thedetection periods may be a normalized weighting coefficient.

Optionally, the multiple different types of sensors include a camera, aradar and/or a laser radar. A dimension corresponding to the camera maybe an image characteristic of the detected target object, a dimensioncorresponding to the radar may be a relative speed of the detectedtarget object with respect to the vehicle, and a dimension correspondingto the laser radar may be a profile of the detected target object.

According to the embodiments of the present disclosure, target objectsaround the vehicle are detected by multiple different types of sensors,and the detection targets representing a same target object, which aredetected by the different types of sensors, are determined by spatialposition matching. With taking the target object as a detection result,the target detection information generated for the detection resultincludes a spatial matching confidence of the detection result in thecurrent detection period, a time matching confidence of the detectionresult, and target detection information on each of the detectiontargets representing the detection result, where the target detectioninformation on the detection target is collected by the sensor detectingthe detection target in a dimension corresponding to the sensor. It canbe seen that, on one hand, the possibility that the detection targetsdetected by different types of sensors presents a same target object canbe determined according to the spatial matching confidence and the timematching confidence, and false detection or missing detection for thetarget object is greatly reduced in view of different advantages ofdifferent sensors. On the other hand, according to the dimensions of thetarget detection information that can be accurately collected by thedifferent types of sensors, target detection information accuratelycollected by different types of sensors in different dimensions is fusedto obtain target detection information on the same target object,thereby providing more accurate and completer target detectioninformation on the target object.

FIG. 9 is a schematic structural diagram of a device for generatingtarget detection information according to an embodiment of the presentdisclosure. In the embodiment, the device 900 may include a processor901, a storage 902, a communication interface 903 and a bus system 904.

The bus system 904 is configured to couple all hardware components ofthe device together.

The communication interface 903 is configured to implement communicationconnection between the device and at least one other device.

The storage 902 is configured to store program instructions and data.

The processor 901 is configured to read the instructions and date storedin the storage 902, to perform steps of:

determining, in a unified plane coordinate system, spatial positions ofinitial detection targets detected by a plurality of different types ofsensors in a current detection period;

matching spatial positions of initial detection targets to be matcheddetected by every two of the plurality of different types of sensors inthe current detection period, and determining the initial detectiontargets under a detection result as result detection targets, whereinspatial positions of any two of the result detection targets under thedetection result are matched with each other; and

generating target detection information of the detection result, whereinthe target detection information of the detection result comprisestarget detection information on each of the result detection targets,which is collected by the sensor detecting the result detection targetin a dimension corresponding to the sensor, and each of the resultdetection targets is the initial detection target detected by thesensor.

Optionally, the processor 901 may be further configured to calculate aspatial matching confidence of the detection result in the currentdetection period based on the number of successful matches among thespatial positions of all the result detection targets in the currentdetection period. The target detection information of the detectionresult further includes the spatial matching confidence of the detectionresult in the current detection period.

Optionally, in order to generate the target detection information of thedetection result, the processor 901 may be further configured togenerate target detection information of the detection result in a casethat the spatial matching confidence of the detection result in thecurrent detection period is greater than a preset spatial confidencethreshold.

Optionally, the processor 901 may be further configured to determine atime matching confidence of the detection result by performing aweighting operation on spatial matching confidences of the detectionresult in multiple recent detection periods. The target detectioninformation of the detection result further includes the time matchingconfidence of the detection result.

Optionally, in order to generate the target detection information of thedetection result, the processor 901 may be further configured togenerate the target detection information of the detection result in acase that the time matching confidence of the detection result isgreater than a preset time confidence threshold.

Optionally, in a case that a Euclidean distance between spatialpositions of two initial detection targets to be matched is within apreset distance threshold, it is determined that the spatial positionsof the two initial detection targets to be matched are matched with eachother.

Optionally, the processor 901 may be further configured to: determine ascreening range in the plane coordinate system based on a current speedof the vehicle; and determine the initial detection targets to bematched based on the screening range. Spatial positions of the initialdetection targets to be matched are located within the screening range.

Optionally, the screening range is a range of all possible spatialpositions passed by the vehicle in a case that a turning radius of thevehicle does not exceed a current radius threshold and a path of thevehicle does not exceed a current path threshold. The current radiusthreshold is determined based on the current speed of the vehicle and alateral acceleration threshold, and the current path threshold isdetermined based on the current speed of the vehicle and a preset timethreshold.

Optionally, the spatial matching confidence of the detection result inthe current detection period may be a ratio of the number of successfulmatches corresponding to the detection result to the total number ofmatches. The number of successful matches corresponding to the detectionresult is the number of successful matches among the spatial positionsof all the result detection targets in the current detection period, andthe total number of matches is the number of matches among all theinitial detection targets to be matched in the current detection period.

Optionally, in order to determine the time matching confidence of thedetection result, the processor 901 may be further configured to obtainthe time matching confidence of the detection result by multiplying thespatial matching confidence in each of the multiple recent detectionperiods with a weighting coefficient corresponding to the detectionperiod and adding the obtained products together. The closer thedetection period is to a current time instant, the greater the weightingcoefficient corresponding to the detection period is.

Optionally, the weighting coefficient corresponding to each of thedetection periods is a normalized weighting coefficient.

Optionally, the multiple different types of sensors include a camera, aradar and/or a laser radar. A dimension corresponding to the camera maybe an image characteristic of the detected target object, a dimensioncorresponding to the radar may be a relative speed of the detectedtarget object with respect to the vehicle, and a dimension correspondingto the laser radar may be a profile of the detected target object.

According to the embodiments of the present disclosure, target objectsaround the vehicle are detected by multiple different types of sensors,and the detection targets representing a same target object, which aredetected by the different types of sensors, are determined by spatialposition matching. With taking the target object as a detection result,the target detection information generated for the detection resultincludes a spatial matching confidence of the detection result in thecurrent detection period, a time matching confidence of the detectionresult, and target detection information on each of the detectiontargets representing the detection result, where the target detectioninformation on the detection target is collected by the sensor detectingthe detection target in a dimension corresponding to the sensor. It canbe seen that, on one hand, the possibility that the detection targetsdetected by different types of sensors presents a same target object canbe determined according to the spatial matching confidence and the timematching confidence, and false detection or missing detection for thetarget object is greatly reduced in view of different advantages ofdifferent sensors. On the other hand, according to the dimensions of thetarget detection information that can be accurately collected by thedifferent types of sensors, target detection information accuratelycollected by different types of sensors in different dimensions is fusedto obtain target detection information on the same target object,thereby providing more accurate and completer target detectioninformation on the target object.

“First” in the terms such as “a first determining unit” in theembodiments of the present disclosure is only used as a name identifierand not indicate first in an order. This rule also adapts to “second”and “third” and so on.

According to the description of the above embodiments, those skilled inthe art may clearly know that all or a part of steps in the methodsaccording to the above embodiments may be performed by means of softwarein combination with a general-purpose hardware platform. Based on suchunderstanding, the technical solution of the present disclosure may beembodied as a computer software product, and the computer softwareproduct may be stored in a storage medium such as a read-only memory(ROM)/RAM, a magnetic disk and an optical disk. The computer softwareproduct includes several instructions to enable a computer device (whichmay be a personal computer, a server or a network communicationapparatus such as a router) to perform the methods described accordingto the embodiments of the present disclosure or some parts of theembodiments.

Various embodiments in the specification are described in a progressivemanner, and each embodiment lays emphasis on differences from otherembodiments. For the same or similar parts between the embodiments, onemay refer to the description of other embodiments. For the methodembodiments and the device embodiments, since they are similar to thesystem embodiment, the description thereof is simple. For the part ofthe method embodiment and the apparatus embodiment related to the systemembodiment, one may refer to the description of the system embodiment.The device embodiments and system embodiments described above are onlyschematic, the modules shown as separate components may be physicallyseparated or not, and components displayed as modules may be physicalmodules or not, that is, the components may be located at a same placeor distributed to multiple network units. The solutions of theembodiment may be achieved by selecting a part or all of the modules asneeded. Those skilled in the art may understand and practice the presentdisclosure without any creative work.

Only the preferred embodiments of the present disclosure are describedabove and are not used to limit the protection scope of the presentdisclosure. It should be noted that, those skilled in the art may makeseveral improvements and modifications without departing the scope ofthe present disclosure, and the improvements and modifications should beregarded as falling within the protection scope of the presentdisclosure.

The invention claimed is:
 1. A method for generating target detectioninformation, comprising: determining, in a unified plane coordinatesystem, spatial positions of initial detection targets detected by aplurality of different types of sensors in a current detection period;matching spatial positions of initial detection targets to be matcheddetected by every two of the plurality of different types of sensors inthe current detection period, and determining the initial detectiontargets under a detection result as result detection targets, whereinspatial positions of any two of the result detection targets under thedetection result are matched with each other; and generating targetdetection information of the detection result, wherein the targetdetection information of the detection result comprises target detectioninformation on each of the result detection targets, which is collectedby the sensor detecting the result detection target in a dimensioncorresponding to the sensor, and wherein each of the result detectiontargets is the initial detection target detected by the sensor.
 2. Themethod according to claim 1, further comprising: calculating a spatialmatching confidence of the detection result in the current detectionperiod based on the number of successful matches among the spatialpositions of all the result detection targets in the current detectionperiod, wherein the target detection information of the detection resultfurther comprises the spatial matching confidence of the detectionresult in the current detection period.
 3. The method according to claim2, wherein generating target detection information of the detectionresult comprises: generating the target detection information of thedetection result in a case that the spatial matching confidence of thedetection result in the current detection period is greater than apreset spatial confidence threshold.
 4. The method according to claim 2,further comprising: determining a time matching confidence of thedetection result by performing a weighting operation on spatial matchingconfidences of the detection result in a plurality of recent detectionperiods, wherein the target detection information of the detectionresult further comprises the time matching confidence of the detectionresult.
 5. The method according to claim 4, wherein generating targetdetection information of the detection result comprises: generating thetarget detection information of the detection result in a case that thetime matching confidence of the detection result is greater than apreset time confidence threshold.
 6. The method according to claim 4,wherein determining the time matching confidence of the detection resultby performing the weighting operation on the spatial matchingconfidences of the detection result in the plurality of recent detectionperiods comprises: adding results obtained by multiplying a spatialmatching confidence in each of the plurality of recent detection periodsby a weighting coefficient corresponding to the detection period, toobtain the time matching confidence of the detection result, wherein thecloser the detection period is to a current time instant, the greaterthe weighting coefficient corresponding to the detection period is. 7.The method according to claim 6, wherein the weighting coefficientcorresponding to each of the detection periods is a normalized weightingcoefficient.
 8. The method according to claim 2, wherein the spatialmatching confidence of the detection result in the current detectionperiod is a ratio of the number of successful matches corresponding tothe detection result to the total number of matches, wherein the numberof successful matches corresponding to the detection result is thenumber of successful matches among the spatial positions of all theresult detection targets in the current detection period, and the totalnumber of matches is the number of matches among all the initialdetection targets to be matched in the current detection period.
 9. Themethod according to claim 1, wherein it is determined that spatialpositions of two of the initial detection targets to be matched arematched with each other, in a case that a Euclidean distance between thespatial positions of the two of the initial detection targets to bematched is within a preset distance threshold.
 10. The method accordingto claim 1, further comprising: determining a screening range in theplane coordinate system based on a current speed of a vehicle; anddetermining the initial detection targets to be matched based on thescreening range, wherein spatial positions of the initial detectiontargets to be matched are within the screening range.
 11. The methodaccording to claim 10, wherein the screening range is a range of allspatial positions able to be passed by the vehicle in a case that aturning radius exceeds a current radius threshold and a path does notexceed a current path threshold, wherein the current radius threshold isdetermined based on the current speed of the vehicle and a lateralacceleration threshold, and the current path threshold is determinedbased on the current speed of the vehicle and a preset time threshold.12. The method according to claim 1, wherein the multiple differenttypes of sensors comprises at least one of a camera, a radar and a laserradar, a dimension corresponding to the camera is an imagecharacteristic of a detected target object, a dimension corresponding tothe radar is a relative speed of the detected target object with respectto the vehicle, and a dimension corresponding to the laser radar is aprofile of the detected target object.
 13. An apparatus for generatingtarget detection information, comprising: a first determining unitconfigured to determine, in a unified plane coordinate system, spatialpositions of initial detection targets detected by a plurality ofdifferent types of sensors in a current detection period; a seconddetermining unit configured to match spatial positions of initialdetection targets to be matched detected by every two of the pluralityof different types of sensors in the current detection period, anddetermine the initial detection targets under a detection result asresult detection targets, wherein spatial positions of any two of theresult detection targets under the detection result are matched witheach other; and a generating unit configured to generate targetdetection information of the detection result, wherein the targetdetection information of the detection result comprises target detectioninformation on each of the result detection targets, which is collectedby the sensor detecting the result detection target in a dimensioncorresponding to the sensor, and each of the result detection targets isthe initial detection target detected by the sensor.
 14. A device forgenerating target detection information, comprising a processor, astorage, a communication interface and a bus system, wherein the bussystem is configured to couple the processor, the storage and thecommunication interface together; the communication interface isconfigured to implement communication connection between the device andat least one other device; the storage is configured to storageinstructions; and the processor is configured to read the instructionsstored in the storage, to perform steps of: determining, in a unifiedplane coordinate system, spatial positions of initial detection targetsdetected by a plurality of different types of sensors in a currentdetection period; matching spatial positions of initial detectiontargets to be matched detected by every two of the plurality ofdifferent types of sensors in the current detection period, anddetermining the initial detection targets under a detection result asresult detection targets, wherein spatial positions of any two of theresult detection targets under the detection result are matched witheach other; and generating target detection information of the detectionresult, wherein the target detection information of the detection resultcomprises target detection information on each of the result detectiontargets, which is collected by the sensor detecting the result detectiontarget in a dimension corresponding to the sensor, and each of theresult detection targets is the initial detection target detected by thesensor.